Articles | Volume 17, issue 15
Atmos. Chem. Phys., 17, 9535–9546, 2017
https://doi.org/10.5194/acp-17-9535-2017
Atmos. Chem. Phys., 17, 9535–9546, 2017
https://doi.org/10.5194/acp-17-9535-2017

Research article 08 Aug 2017

Research article | 08 Aug 2017

Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks

Hendrik Andersen et al.

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Cited articles

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Short summary
Aerosol-cloud interactions continue to contribute large uncertainties to our climate system understanding. In this study, we use near-global satellite and reanalysis data sets to predict marine liquid-water clouds by means of artificial neural networks. We show that on the system scale, lower-tropospheric stability and boundary layer height are the main determinants of liquid-water clouds. Aerosols show the expected impact on clouds but are less relevant than some meteorological factors.
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